Le mood, un nouvel instrument au service de l'analyse dynamique des opinions :Application aux évolutions de la xénophobie en France (1999-2009).

Le présent article répond à deux objectifs. Premièrement il s’agit d’exposer une méthode statistique permettant un suivi dans le temps des évolutions de l’opinion publique là où trop souvent les chercheurs sont confrontés à des données incomplètes et des ruptures de séries. Cette méthode est celle du public policy mood inventée aux États-Unis par James Stimson. Deuxièmement, à partir de cette méthode, nous avons alors construit un indice longitudinal de tolérance aux immigrés sur la base du baromètre de la CNCDH et avons proposé d’en analyser les évolutions. L’opinion a considérablement évolué vers plus de tolérance entre 1990 et 2009 et ces évolutions ne peuvent pas seulement être expliquées par le renouvellement générationnel. Les préjugés xénophobes obéissent à la théorie thermostatique de l’opinion et évoluent désormais selon la couleur politique du gouvernement.This article serves two main objectives. Firstly, we present a statistical method designed to track long-term public opinion trends and cope with incomplete and irregular series breakdowns, an enduring problem in this field of research. This method, invented by James Stimson in the US, is widely associated with the concept of the “public policy mood”. Secondly, based on this method we have constructed a “tolerance-towards-immigration” mood index based on CNCDH (French National Consultative Commission on Human Rights) barometer survey and tried to track its development over time. It turns out that the French public grew increasingly tolerant towards immigrants during the period from 1990 to 2009, and that trend cannot be explained solely by generational renewal. We argue that prejudice levels now obey the thermostatic theory and vary according to the current administration’s political leanings

Le mood, un nouvel instrument au service de l'analyse dynamique des opinions :Application aux évolutions de la xénophobie en France (1999-2009).

Le présent article répond à deux objectifs. Premièrement il s’agit d’exposer une méthode statistique permettant un suivi dans le temps des évolutions de l’opinion publique là où trop souvent les chercheurs sont confrontés à des données incomplètes et des ruptures de séries. Cette méthode est celle du public policy mood inventée aux États-Unis par James Stimson. Deuxièmement, à partir de cette méthode, nous avons alors construit un indice longitudinal de tolérance aux immigrés sur la base du baromètre de la CNCDH et avons proposé d’en analyser les évolutions. L’opinion a considérablement évolué vers plus de tolérance entre 1990 et 2009 et ces évolutions ne peuvent pas seulement être expliquées par le renouvellement générationnel. Les préjugés xénophobes obéissent à la théorie thermostatique de l’opinion et évoluent désormais selon la couleur politique du gouvernement.This article serves two main objectives. Firstly, we present a statistical method designed to track long-term public opinion trends and cope with incomplete and irregular series breakdowns, an enduring problem in this field of research. This method, invented by James Stimson in the US, is widely associated with the concept of the “public policy mood”. Secondly, based on this method we have constructed a “tolerance-towards-immigration” mood index based on CNCDH (French National Consultative Commission on Human Rights) barometer survey and tried to track its development over time. It turns out that the French public grew increasingly tolerant towards immigrants during the period from 1990 to 2009, and that trend cannot be explained solely by generational renewal. We argue that prejudice levels now obey the thermostatic theory and vary according to the current administration’s political leanings

The Moving Centre: Preferences for Government Activity in Britain, 1950–2005

The political ‘centre’ is often discussed in debates about public policy and analyses of party strategies and election outcomes. Yet, to date, there has been little effort to estimate the political centre outside the United States. This article outlines a method of estimating the political centre using public opinion data collected for the period between 1950 and 2005. It is demonstrated that it is possible to measure the centre in Britain, that it moves over time, that it shifts in response to government activity and, furthermore, that it has an observable association with general election outcomes.</jats:p

The Least Dangerous Branch Revisited: New Evidence on Supreme Court Responsiveness to Public Preferences

With competing assumptions and alternative empirical models, scholars have come to rather different conclusions about the impact of public preferences on the decisions of the U.S. Supreme Court. Some have found the justices to be attentive to mass opinion, while others have judged it to be irrelevant. Across this divide, however, one assumption is widely shared; that is, political scientists generally agree upon how best to measure the Court's outputs. In this analysis, we employ an alternative estimate of the justices’ liberalism, one which we think better reflects the underlying ideological tenor of their policies. With data from 1953 to 1996, we compare time-series models using different indicators of the Supreme Court's aggregate liberalism. Our results suggest that, in addition to being motivated by their own preferences, the justices are highly responsive to public mood, as well

Transmission analysis of a large tuberculosis outbreak in London:a mathematical modelling study using genomic data

Outbreaks of tuberculosis (TB) - such as the large isoniazid-resistant outbreak centred on London, UK, which originated in 1995 - provide excellent opportunities to model transmission of this devastating disease. Transmission chains for TB are notoriously difficult to ascertain, but mathematical modelling approaches, combined with whole-genome sequencing data, have strong potential to contribute to transmission analyses. Using such data, we aimed to reconstruct transmission histories for the outbreak using a Bayesian approach, and to use machine-learning techniques with patient-level data to identify the key covariates associated with transmission. By using our transmission reconstruction method that accounts for phylogenetic uncertainty, we are able to identify 21 transmission events with reasonable confidence, 9 of which have zero SNP distance, and a maximum distance of 3. Patient age, alcohol abuse and history of homelessness were found to be the most important predictors of being credible TB transmitters

Gender Difference or Parallel Publics? The Dynamics of Defense Spending Opinions in the United States, 1965-2007

Gender is now recognized as an important dividing line in American political life, and scholars have accumulated evidence that national security issues are an important reason for gender differences in policy preferences. We therefore expect that the dynamics of support for defense spending among men and women will differ. In contrast, several scholars have shown that population subgroups exhibit a ‘‘parallel’’ dynamic in which the evolution of their preferences over time is very similar, despite differences in the average level of support. Unfortunately, there is little time series evidence on gendered reactions to policy, including defense spending, that would allow one to arbitrate between these competing perspectives. In this research note, we assemble a time series of support for defense spending among men and women and model the determinants of that support for the period 1967–2007. We find that women are on average less supportive of defense spending than are men. However, we also find that the over time variation of support for defense spending among men and women is very similar—each is conditioned principally by the past year’s change in defense spending and occasionally by war casualties and a trade-off between defense and civilian spending

The impact of testing and infection prevention and control strategies on within-hospital transmission dynamics of COVID-19 in English hospitals.

Nosocomial transmission of SARS-CoV-2 is a key concern, and evaluating the effect of testing and infection prevention and control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical English hospital, we estimate that between 9 March 2020 and 17 July 2020 approximately 20% of infections in inpatients, and 73% of infections in healthcare workers (HCWs) were due to nosocomial transmission. Model results suggest that placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 35%. Periodic testing of HCWs has a smaller effect on the number of hospital-acquired COVID-19 cases in patients, but reduces infection in HCWs by as much as 37% and results in only a small proportion of staff absences (approx. 0.3% per day). This is considerably less than the 20-25% of staff that have been reported to be absent from work owing to suspected COVID-19 and self-isolation. Model-based evaluations of interventions, informed by data collected so far, can help to inform policy as the pandemic progresses and help prevent transmission in the vulnerable hospital population. This article is part of the theme issue 'Modelling that shaped the early COVID-19 pandemic response in the UK'

The impact of testing and infection prevention and control strategies on within-hospital transmission dynamics of COVID-19 in English hospitals

Nosocomial transmission of SARS-CoV-2 is a key concern, and evaluating the effect of testing and infection prevention and control strategies is essential for guiding policy in this area. Using a within-hospital SEIR transition model of SARS-CoV-2 in a typical English hospital, we estimate that between 9 March 2020 and 17 July 2020 approximately 20% of infections in inpatients, and 73% of infections in healthcare workers (HCWs) were due to nosocomial transmission. Model results suggest that placing suspected COVID-19 patients in single rooms or bays has the potential to reduce hospital-acquired infections in patients by up to 35%. Periodic testing of HCWs has a smaller effect on the number of hospital-acquired COVID-19 cases in patients, but reduces infection in HCWs by as much as 37% and results in only a small proportion of staff absences (approx. 0.3% per day). This is considerably less than the 20–25% of staff that have been reported to be absent from work owing to suspected COVID-19 and self-isolation. Model-based evaluations of interventions, informed by data collected so far, can help to inform policy as the pandemic progresses and help prevent transmission in the vulnerable hospital population. This article is part of the theme issue ‘Modelling that shaped the early COVID-19 pandemic response in the UK’